Hybrid metaheuristics using rough sets for QoS-aware service composition
Document Type
Article
Publication Date
1-1-2022
Abstract
Quality of Service (QoS)-aware service composition plays an increasingly important role in various computational paradigms and delivery models, predominantly cloud computing. The proliferation of services with expanding quality attributes navigates this problem towards big service compositions, which fall under the umbrella of NP-hard. Within the realm of big services, performing composition also became a computationally expensive and challenging task. Since service composition is an NP-hard problem, numerous research aimed to determine optimal or near-optimal solutions within a reasonable computation budget. A large body of evidence suggests that metaheuristics could realize this goal to some extent. However, the proliferation of services with expanding quality attributes (search dimensions) may fail the most efficient techniques. In order to deal with the problem of big service composition, one trending approach has been devising hybrid metaheuristics methods by incorporating clustering techniques to minimize search space. This paper proposes a hybrid metaheuristic incorporated with a maximal discernibility heuristic based on rough set theory to perform composition in the subset of search space. Moreover, it introduces a parallel processing and monitoring mechanism to provide immunity against premature convergence when the search space is minimized. The experiment was conducted for 25 datasets generated incrementally from a real-world QWS dataset, where the proposed hybrid solution effectively improves solution quality and reduces execution time with a statistical significance of 99 % confidence interval across diverse metaheuristics and datasets.
Keywords
Metaheuristics, Cloud computing, Quality of service, Search problems, Rough sets, Convergence, Cloud computing, Quality of service, Service composition, Metaheuristics, Hybrid metaheuristics, Rough sets
Divisions
fsktm
Funders
Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme [FRGS/1/2021/ICT11/UM/02/1 (FP005-2021)]
Publication Title
IEEE Access
Volume
10
Publisher
Institute of Electrical and Electronics Engineers
Publisher Location
445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA